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Hurricanes are powerful agents of destruction with significant socioeconomic impacts. A persistent problem due to the large-scale evacuations during hurricanes in the southeastern United States is the fuel shortages during the evacuation. Computational models can aid in emergency preparedness and help mitigate the impacts of hurricanes. In this paper, we model the hurricane fuel shortages using the SIR epidemic model. We utilize the crowd-sourced data corresponding to Hurricane Irma and Florence to parametrize the model. An estimation technique based on Unscented Kalman filter (UKF) is employed to evaluate the SIR dynamic parameters. Finally, an optimal control approach for refueling based on a vaccination analogue is presented to effectively reduce the fuel shortages under a resource constraint. We find the basic reproduction number corresponding to fuel shortages in Miami during Hurricane Irma to be 3.98. Using the control model we estimated the level of intervention needed to mitigate the fuel-shortage epidemic. For example, our results indicate that for Naples- Fort Myers affected by Hurricane Irma, a per capita refueling rate of 0.1 for 2.2 days would have reduced the peak fuel shortage from 55% to 48% and a refueling rate of 0.75 for half a day before landfall would have reduced to 37%. [ABSTRACT FROM AUTHOR]

The insurance industry has used parametric solutions to transfer catastrophe risks since the 1990s. Instead of relying on a lengthy process to assess a claim, these products pay the insured a pre-agreed amount if the physical characteristics of the event fulfill pre-defined conditions. Cat-in-a-box or cat-in-a-circle triggers, commonly used tools for tropical cyclone risk transfer, provide a payout to the insured if the track of a hurricane crosses the perimeter of a geographic area defined by a polygon or a circle with a certain intensity. Cat-in-a-grid solutions are novel and more sophisticated. They rely on a set of multiple cat-in-a-box triggers arranged on an orthogonal grid. The consideration of multiple geographic domains instead of a single box or circle is helpful to reduce basis risk, i.e., the difference between the parametric loss estimate and the target loss. In the case study for Miami presented here, for instance, a cat-in-a-grid solution showed 18.5% less basis risk than a typical cat-in-a-box alternative. To organize the different types of triggers within a common framework, we classify the existing alternatives based on whether they use a single geographic domain (like a box or a circle) or multiple domains (like a grid). We discuss their advantages and disadvantages and describe the process required to calibrate any one solution with the help of a catastrophe-risk model. We focus, in particular, on the analysis and construction of cat-in-a-grid triggers, the alternative that we believe offers the greatest potential for global standardization and adoption. [ABSTRACT FROM AUTHOR]

Coastal cities in the east and southeast regions of the US have seen significant population growth and economic development in the last 2 decades. As a result, urban infrastructure, populations, and economies are becoming increasingly vulnerable to hurricane-driven hazards. Criteria for wind design in national standards are intended specifically for the design and performance assessment of individual buildings and other facilities for life safety. They are not adequate for assessing community resilience because hurricane winds are spatially nonuniform. Although scenario-based approaches to representing hurricane demands are more useful in community performance assessment because the distinct features of various hurricane scenarios and their impact on a community can be captured, they are not tied to a specific hazard level. This study introduces a new method for systematically identifying a set of hurricane scenarios corresponding to a stipulated return period (RP) for resilience assessment of coastal communities using a deaggregation approach, which establishes a connection that has not existed previously between hurricane scenarios and the building regulatory process. A community patterned after Miami, Florida, was used to demonstrate the proposed hazard deaggregation and damage analysis. Hurricane scenario events that are dominant contributors to the stipulated RP events, coupled with fragility models of engineered buildings, were used to identify building damage patterns and form an improved basis for risk-informed decision making. [ABSTRACT FROM AUTHOR]

The accurate interpretation of hurricane risk graphics is expected to benefit public decision-making. To investigate public interpretation and suggest improvements to graphical designs, an interdisciplinary, mixed-methods approach is being undertaken. Drawing on a series of focus groups with Miami residents that focused on understanding interpretations of the National Hurricane Center's (NHC) track forecast cone or "Cone of Uncertainty," we developed an online survey targeting a much larger sample of Florida residents (n = 2,847). The findings from this survey are the primary focus of this short article. We attempt to answer three questions: 1) What are the most frequent and trusted sources of information that Florida residents use when they learn that a hurricane is coming their way? 2) How accurately are Florida residents able to interpret risk based on the NHC Cone of Uncertainty graphic? 3) What is the relationship, if any, between the number of correct interpretations and income, age, education, housing location, housing type, or "most trusted" sources of information? Unlike previous public surveys that focused more on evacuation decisions, forecast usage, and perception of hurricane risk, our approach specifically pays attention to the details of design elements of the forecast graphics with the long-term goal of minimizing misinterpretation of future graphics. Our analysis suggests that many residents have difficulty interpreting several aspects, suggesting a rethink on how to graphically communicate aspects such as uncertainty, the size of the storm, areas of likely damage, watches and warnings, and wind intensity categories. Graphical communication strategies need to be revised to better support the different ways in which people understand forecast products, and these strategies should be tested for validity in real world settings. [ABSTRACT FROM AUTHOR]

Modeling and estimating the damage to the built environment caused by hurricane winds is an essential requirement to enhance community resilience. Consideration of damage to a building's envelope caused by windborne debris impact is necessary. To model this damage for a certain subdivision of houses, debris generated in neighboring subdivisions, defined as exogenous debris, must be taken into account. Existing physics-based damage estimation models do not consider the effect exogenous windborne debris has on the estimated damage due to hurricane winds. This paper provides a methodology to identify the extent of the neighboring subdivisions that needs to be considered during damage simulation to accurately account for exogenous windborne debris. The presented methodology is based on first identifying the extent of the neighboring subdivisions through a simulation-based strategy which follows an iterative scheme. For each size increment, the iterative scheme estimates the number of exogenous windborne debris using a physics-based damage estimation model. The single building solution is then generalized to a subdivision of any arbitrary shape. The proposed methodology is applied to analyze a hypothetical residential community in Miami, FL. Analysis results show the effect on the required extent of the neighboring subdivisions of the hurricane maximum wind speed, the floor-area ratio and the resistance of the building envelope components. The analysis concludes with a regression model that can be used to estimate the size of the neighboring subdivisions to be used in damage estimation models. • A methodology to model exogenous windborne debris during hurricanes is presented. • The proposed methodology solves for a subdivision of any arbitrary boundary. • The methodology accounts for factors related to the neighboring subdivisions. • The methodology accounts for factors related to the hurricane hazard. • A regression model is presented to account for exogenous windborne debris. [ABSTRACT FROM AUTHOR]

Abstract: The paper presents an experimental study to assess wind induced pressure on full-scale loose concrete roof pavers by using Wall of Wind, a large-scale hurricane testing facility at Florida International University. Experimental tests were conducted on full-scale concrete pavers mounted on a test building to evaluate wind-induced external and underneath pressures acting on the pavers. The study shows that roof pavers could be subjected to significant uplifting wind forces due to negative pressures. In corner and edge areas of the roof, pressure differences produced net uplift on the pavers, at design wind speed, that was greater than the individual weight of the pavers. The study provides new insights by testing the actual roofing material at high wind speeds in a controlled environment and also showed that locking the pavers together can mitigate the issues at corners and edges by increasing the weight of the pavers that acts together to counterbalance the net uplift pressure. [Copyright &y& Elsevier]

Hurricane Matthew (2016) was observed by the ground-based polarimetric Next Generation Weather Radar (NEXRAD) in Miami (KAMX) and the National Oceanic and Atmospheric Administration WP-3D (NOAA P-3) airborne tail Doppler radar near the coast of the southeastern United States for several hours, providing a novel opportunity to evaluate and compare single- and multiple-Doppler wind retrieval techniques for tropical cyclone flows. The generalized velocity track display (GVTD) technique can retrieve a subset of the wind field from a single ground-based Doppler radar under the assumption of nearly axisymmetric rotational wind, but it has been shown to have errors from the aliasing of unresolved wind components. An improved technique that mitigates errors due to storm motion is derived in this study, although some spatial aliasing remains due to limited information content from the single-Doppler measurements. A spline-based variational wind retrieval technique called SAMURAI can retrieve the full three-dimensional wind field from airborne radar fore–aft pseudo-dual-Doppler scanning, but it has been shown to have errors due to temporal aliasing from the nonsimultaneous Doppler measurements. A comparison between the two techniques shows that the axisymmetric tangential winds are generally comparable between the two techniques, and the improved GVTD technique improves the accuracy of the retrieval. Fourier decomposition of asymmetric kinematic and convective structure shows more discrepancies due to spatial and temporal aliasing in the retrievals. The strengths and weaknesses of each technique for studying tropical cyclone structure are discussed and suggest that complementary information can be retrieved from both single- and dual-Doppler retrievals. Future improvements to the asymmetric flow assumptions in single-Doppler analysis and steady-state assumptions in pseudo-dual-Doppler analysis are required to reconcile differences in retrieved tropical cyclone structure. [ABSTRACT FROM AUTHOR]

A statistical procedure for estimating the risk of strong winds from hurricanes is demonstrated and applied to several major cities in Florida. The procedure, called the hurricane risk calculator, provides an estimate of wind risk over different length periods and can be applied to any location experiencing this hazard. Results show that the city of Miami can expect to see hurricane winds blowing at 50 m s−1 [45.5-54.5 m s−1 is the 90% confidence interval (CI)] or stronger, on average, once every 12 yr. In comparison, the city of Pensacola can expect to see hurricane winds of 50 m s−1 (46.9-53.1 m s−1, 90% CI) or stronger once every 24 yr. A quantile regression is applied to hurricane wind speeds in the vicinity of Florida. Results show that the strongest hurricanes are getting stronger as a consequence of higher offshore intensification rates. [ABSTRACT FROM AUTHOR]